Autocorrelation vs Multicollinearity - What's the difference?
autocorrelation | multicollinearity |
(statistics, signal processing) The cross-correlation of a signal with itself: the correlation between values of a signal in successive time periods.
* {{quote-book, 1990, K. Holden, D. Peel & John L. Thompson, Economic Forecasting
, passage=Dividing the covariances by the variance gives the autocorrelations .}}
(statistics) A phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, so that the coefficient estimates may change erratically in response to small changes in the model or data.
As nouns the difference between autocorrelation and multicollinearity
is that autocorrelation is the cross-correlation of a signal with itself: the correlation between values of a signal in successive time periods while multicollinearity is a phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, so that the coefficient estimates may change erratically in response to small changes in the model or data.autocorrelation
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